With applications ranging from diagnostic procedures to radiation therapy, the importance of high-performance medical imaging is immeasurable. As such, new advanced medical imaging technologies continue to be developed.
Numerous modalities currently exist for medical imaging, including: ultrasound, magnetic resonance imaging, x-ray, computed tomography, positron emission tomography, etc. Such modalities may comprise either film-based or digital imaging systems, with digital imaging systems representing the future of medical imaging. Digital imaging systems produce far more accurate and detailed images of an object than conventional film-based imaging systems, and also allow further enhancements of the images to be made once an object is scanned. While the quantity and quality of imaging modalities has recently exploded, an increasing number of patients are now having repeat imaging examinations, either in the same modality or in different modalities. Additionally, it is now possible to use information from prior imaging examinations to determine patient information for use in prescribing new imaging examinations and selecting data acquisition protocols therefor.
Each imaging technique, whether film-based or digital, requires various data acquisition protocols to be selected and input to the medical imaging device prior to scanning the patient to acquire an image. Generally, these data acquisition protocols are selected by a scanner technician, who inputs various information about a patient into the system, evaluates the information, and then selects an appropriate protocol based thereon. Inputting this information into a system is prone to errors. Additionally, selecting an appropriate protocol is highly subjective, and therefore, it is difficult to train technicians on optimal protocol selection. As the quality of the resulting scan or image is often highly dependent upon the information that is input and the data acquisition protocol that is selected, it would be beneficial to have a way to automatically transfer patient information to a scanner, as well as select an optimal patient-centric data acquisition protocol for each patient, thereby removing the proneness to errors and subjectivity of the data acquisition protocol selection process.